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1.
Curr Biol ; 25(3): 342-347, 2015 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-25619761

RESUMO

Cross-flows (winds or currents) affect animal movements [1-3]. Animals can temporarily be carried off course or permanently carried away from their preferred habitat by drift depending on their own traveling speed in relation to that of the flow [1]. Animals able to only weakly fly or swim will be the most impacted (e.g., [4]). To circumvent this problem, animals must be able to detect the effects of flow on their movements and respond to it [1, 2]. Here, we show that a weakly swimming organism, the jellyfish Rhizostoma octopus, can orientate its movements with respect to currents and that this behavior is key to the maintenance of blooms and essential to reduce the probability of stranding. We combined in situ observations with first-time deployment of accelerometers on free-ranging jellyfish and simulated the behavior observed in wild jellyfish within a high-resolution hydrodynamic model. Our results show that jellyfish can actively swim countercurrent in response to current drift, leading to significant life-history benefits, i.e., increased chance of survival and facilitated bloom formation. Current-oriented swimming may be achieved by jellyfish either directly detecting current shear across their body surface [5] or indirectly assessing drift direction using other cues (e.g., magnetic, infrasound). Our coupled behavioral-hydrodynamic model provides new evidence that current-oriented swimming contributes to jellyfish being able to form aggregations of hundreds to millions of individuals for up to several months, which may have substantial ecosystem and socioeconomic consequences [6, 7]. It also contributes to improve predictions of jellyfish blooms' magnitude and movements in coastal waters.


Assuntos
Modelos Biológicos , Cifozoários/fisiologia , Natação/fisiologia , Movimentos da Água , Acelerometria , Animais , Fenômenos Biomecânicos , Simulação por Computador , Comportamento de Massa , Orientação/fisiologia , Fatores de Tempo
2.
PLoS One ; 8(10): e76739, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-24204666

RESUMO

The migratory shorebirds of the East Atlantic flyway land in huge numbers during a migratory stopover or wintering on the French Atlantic coast. The Brouage bare mudflat (Marennes-Oléron Bay, NE Atlantic) is one of the major stopover sites in France. The particular structure and function of a food web affects the efficiency of carbon transfer. The structure and functioning of the Brouage food web is crucial for the conservation of species landing within this area because it provides sufficient food, which allows shorebirds to reach the north of Europe where they nest. The aim of this study was to describe and understand which food web characteristics support nutritional needs of birds. Two food-web models were constructed, based on in situ measurements that were made in February 2008 (the presence of birds) and July 2008 (absence of birds). To complete the models, allometric relationships and additional data from the literature were used. The missing flow values of the food web models were estimated by Monte Carlo Markov Chain--Linear Inverse Modelling. The flow solutions obtained were used to calculate the ecological network analysis indices, which estimate the emergent properties of the functioning of a food-web. The total activities of the Brouage ecosystem in February and July are significantly different. The specialisation of the trophic links within the ecosystem does not appear to differ between the two models. In spite of a large export of carbon from the primary producer and detritus in winter, the higher recycling leads to a similar retention of carbon for the two seasons. It can be concluded that in February, the higher activity of the ecosystem coupled with a higher cycling and a mean internal organization, ensure the sufficient feeding of the migratory shorebirds.


Assuntos
Migração Animal/fisiologia , Aves/fisiologia , Ecossistema , Cadeia Alimentar , Animais , Oceano Atlântico , Bactérias/crescimento & desenvolvimento , Baías , França , Geografia , Invertebrados/crescimento & desenvolvimento , Cadeias de Markov , Modelos Biológicos , Método de Monte Carlo , Estações do Ano
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